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Claim

Sketch ⋆-Metric: Comparing Data Streams via Sketching

descriptionPublicationkeyboard_double_arrow_right Article , Conference object , Report 01 Aug 2013 France Publisher:IEEEJournal:2013 IEEE 12th International Symposium on Network Computing and Applications
Authors: Anceaume, Emmanuelle; Busnel, Yann;

doi: 10.1109/nca.2013.11

Sketch ⋆-Metric: Comparing Data Streams via Sketching

Abstract

In this paper, we consider the problem of estimating the distance between any two large data streams in small-space constraint. This problem is of utmost importance in data intensive monitoring applications where input streams are generated rapidly. These streams need to be processed on the fly and accurately to quickly determine any deviance from nominal behavior. We present a new metric, the Sketch ⋆-metric, which allows to define a distance between updatable summaries (or sketches) of large data streams. An important feature of the Sketch ⋆-metric is that, given a measure on the entire initial data streams, the Sketch ⋆-metric preserves the axioms of the latter measure on the sketch. Extensive experiments conducted on both synthetic traces and real data sets allow us to validate the robustness and accuracy of the Sketch ⋆-metric

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France
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Keywords

[INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], 330, metric, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], randomized approximation algorithm, randomized approxima- tion algorithm, 620, 004, Divergence, [MATH.MATH-IT] Mathematics [math]/Information Theory [math.IT], [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], [INFO.INFO-GT] Computer Science [cs]/Computer Science and Game Theory [cs.GT], Data stream, Randomized approximation algorithm, [INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT]

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    popularity
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
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